geoarray 0.15.2

Fast Python interface for geodata - either on disk or in memory.

Fast Python interface for geodata - either on disk or in memory.

The geoarray package facilitates reading and writing of all GDAL compatible image file formats and provides functions for geospatial processing.

• Free software: Apache 2.0

• Documentation: https://danschef.git-pages.gfz-potsdam.de/geoarray/doc/

Status

See also the latest coverage report and the nosetests HTML report.

Features and usage

• There is an example notebook that shows how to use geoarray: here.

Installation

Using Anaconda or Miniconda (recommended)

Using conda (latest version recommended), geoarray is installed as follows:

1. Create virtual environment for geoarray (optional but recommended):

   $ conda create -c conda-forge --name geoarray python=3
   $ conda activate geoarray

2. Then install geoarray itself:

   $ conda install -c conda-forge geoarray

This is the preferred method to install geoarray, as it always installs the most recent stable release and automatically resolves all the dependencies.

Using pip (not recommended)

There is also a pip installer for geoarray. However, please note that geoarray depends on some open source packages that may cause problems when installed with pip. Therefore, we strongly recommend to resolve the following dependencies before the pip installer is run:

• cartopy

• gdal >=2.1.0

• geopandas

• holoviews # optional, in case you want to use interactive plotting

• matplotlib

• numpy

• pandas

• pyproj >2.2.0

• scikit-image

• shapely

Then, the pip installer can be run by:

$ pip install geoarray

If you don’t have pip installed, this Python installation guide can guide you through the process.

History / Changelog

You can find the protocol of recent changes in the geoarray package here.

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.